Deep generation of synthetic training data for the automated extraction of semantic knowledge from historical maps

Category

Published in:

Abstracts of the ICA
Vol. 7.2024 (02.09.2024), art. no. 7, p. 1-2

Volume:

7.2024

Publication date:

02.09.2024

URN:

urn:nbn:de:0307-20250822-003-5

DOI:

10.5194/ica-abs-7-7-2024

Language:

English

Type of Resource:

Text

Extent:

1 Online-Ressource (Seite 1-2, 7,00 MB) : 3 Illustrationen, 1 Textdatei (PDF)

Keywords:

historical maps; generative adversarial network; training data generation; cartographic heritage; Historische Karte^GND; erzeugendes gegnerisches Netzwerk; Trainingsdaten-Generierung; kartografisches Erbe

DDC subject of DNB:

520 Astronomy & allied sciences

URL:

https://doi.org/10.5194/ica-abs-7-7-2024

URL:

https://ica-abs.copernicus.org/articles/7/7/2024/

Link to Raw Object:

https://ica-abs.copernicus.org/articles/7/7/2024/ica-abs-7-7-2024.pdf

Hosting institution:

HafenCity University Hamburg (HCU) [DE]

Statement of responsibility:

Lukas Arzoumanidis, James Ormond Fethers, Sethmiya Herath Mudiyanselage, Youness Dehbi

Bibliographic notes:

Published in: Abstracts of the ICA, Volume 7, 2024 - European Cartographic Conference – EuroCarto 2024; 9–11 September 2024, TU Wien, Vienna, Austria; Editors: Georg Gartner, Florian Ledermann, and Andrea Binn | https://ica-abs.copernicus.org/articles/7/index.html